Combined Nitrogen and Phosphorus Removal. Model-Based Process Optimization

Combined Nitrogen and Phosphorus Removal. Model-Based Process Optimization 1

Combined Nitrogen and Phosphorus Removal. Model-Based Process Optimization

Noelia Alasino, Miguel C. Mussati, Nicolás Scenna, Pío Aguirre

INGAR Instituto de Desarrollo y Diseño (CONICET-UTN), Avellaneda 3657, (S3002GJC) Santa Fe, Argentina.

Abstract

An optimization model based on a superstructure embedding several activated sludge process configurations for nutrient removal is formulated and solved. Simultaneous optimization of the process configuration (process synthesis) and operation conditions for given wastewater specifications and influent flow rate in steady state operation are investigated. The performance criteria selected is the total annual operation cost minimization while predicting compliance with the effluent permitted limits. As the piece of equipment is supposed given, investment costs are not considered.The Activated Sludge Model No. 3 extended with the Bio-P module for computing biological phosphorus removal are used to model the reaction compartments, and the Takács model for representing the secondary settler. The resulting mathematical model is a highly non-linear system, formulated as a Non-Linear-Programming Problem, specifically asa DNLP. The model is implemented and solved using GAMS and CONOPT,respectively.The optimal solution computed from the superstructure model provides cost improvements of around10% with respect to conventional processes.

Keywords: Activated sludge process, ASM3+BioP,process optimization,superstructure, DNLP.

1. Introduction

In previous works, the COST benchmark wastewater treatment plant model (Copp, 2002)to evaluate control strategies for N removal based on the Activated Sludge Model No. 1 had been used as starting point for optimization of the operation conditions as well as for synthesis of activated sludge WWTPs. Based on the ASM3 model (Gujer et al, 1999), the aim was to minimize the total annual operating cost (Alasino et al, 2006a and 2006b) and the total cost (investments and operating costs) (Alasino et al, 2007).

Optimization of Premoval facilities is nowadays a key issue. Indeed, biological P removal is often persuade in European treatment plants as an alternative to chemical P removal based on P precipitation with salts such as FeCl3(Gernaey and Jorgensen, 2004). In Gernaey and Jorgensen (2004) a benchmark WWTP for combined N and P removal is developed for evaluating and comparing WWTP control strategies, and a number of scenario evaluations focusing on the selection of DO set points are described to illustrate the simulation benchmark.

Here, optimal operation conditions for a superstructure embedding the most widely used configurations for combined nutrient removal aiming at minimizing operating annual costs will be investigated for given wastewater specifications and flow rate. The plant lay-out used as the departing model is that proposed by Gernaey and Jorgensen (2004), which corresponds to the A2/O process. The other configurations embedded are the UCT process (VIP process), the modified UCT process and the Bardenpho process.

2. Problem Definition

The problem addressed is the simultaneous optimization of the process configuration (process synthesis) and the operating conditions (flowrates of aeration, recycles and fresh feed to each reaction compartment and external carbon source dosage) of ASWWTPs for combined biological N and P removal, aiming at minimizing the total annual operating cost.It is assumed: - influent wastewater specifications, - effluent permitted limits, - a process superstructure model, - a cost model computing operation costs, and - process unit sizes.

1. Process Description

Figure 1. Most widely used ASWWTP configurations for combined nutrient removal

In ASPs, the WW stream is exposed to different environmental conditions (anaerobic, anoxic and aerated zones) to facilitate the different microbiological processes such as the release or uptake of P, nitrification and denitrification.Reduction of carbonaceous matter and nitrification (ammonium is converted to nitrate by autotrophs) are favored by aerobic conditions; while denitrification (nitrate is converted to N gas by heterotrophs) is favored by anoxic ones, if readily biodegradable C is available.Biological P removal relies on P uptake by aerobic heterotrophs (known as phosphate-accumulating organisms PAOs) capable of storing orthophosphate in excess of their biological growth requirements. Under anaerobic conditions, PAOs convert readily available C (e.g., VFAs) to C compounds called polyhydroxyalkanoates PHAs. PAOs use energy generated through the breakdown of polyphosphate molecules to create PHAs. This breakdown results in P release.Under subsequent aerobic or anoxic conditions, PAOs use the stored PHAs as energy to take up the P that was released in the anaerobic zone, as well as any additional phosphate present in the WW.

Figure 1 presents the most widely used ASWWTP configurations for combined N and P removal. The A2/O process presents a sequence of anaerobic reactors (to promote the growth of PAOs) followed by a sequence of anoxic to promote denitrification, and finally aerobic reactors. It has one internal and one external recycle stream. The internal recycle stream conducts a fraction of the nitrified liquor from the last aerobic to the 1stanoxic compartment, and the external recycle conducts a fraction of the sludge from the underflow of the sedimentation tank to the 1stcompartment. In the UCT process, both recycle streams are feed to the anoxic zone and a second internal recycle stream is present from the anoxic to the anaerobic compartment. The modified UCT process has 2 internal recycles and 1 external one as in the original UCT process but the anoxic zone is divided into 2 zones. The external recycle is directed from the underflow of the decanter to the 1stanoxic zone. The 1stinternal recycle stream conducts a fraction of the nitrified liquor from the aerobicto the 2ndanoxic zone. Finally, the second internal recycle stream pumps a fraction of the mixed liquor from the 1stanoxic back to the anaerobiccompartment. The Bardenpho process configuration has also an external recycle from the sedimentation tank to the anaerobic zone and has an internal recycle from the 1staerobic zone to the 1stanoxic zone.In general, the addition of external C tothe anoxic zone could be detrimental to P removal in a EBPR plant, as the ordinary heterotrophs have competing advantages for nitrate over the denitrifying PAOs, resulting in poor anoxic P uptake. It is recommendable that the external C to be added to the anaerobic zone of an EBPR plant short of COD. The C source is taken up by PAOs to form intracellular C storage compounds, the use of which improves both P and N removal under anoxic conditions.

1. ProcessOptimization Model

The superstructure embeds the four process alternatives described in the preceding section as can be appreciate in Figure 2. As mentioned, the basic plant adopted as starting point for developing the superstructure model is that proposed by Gernaey and Jorgensen (2004), which consists of 7 mixed reaction compartments with a total volume of 6749 m3, and 1 secondary settler of 6000 m3. The 1st and 2nd compartments are anaerobic units; the following 2 are anoxic zones and the last 3 formed the aerated region. This configuration has 1 internal and 1 external recycle stream, and corresponds to the A2/O process. The other process configurations are incorporated into the superstructure by allowing more recycles streams. The superstructure also allowed the distribution of the main process streams.

Figure 2. Proposed superstructure

4.1.Reactor model

For the aeration tanks, steady state CSTR model is considered. The ASM3 model (Gujer et al, 1999) extended with the Bio-P module (Rieger et al., 2001) is chosen to model the biological processes.The stoichiometric coefficients and kinetic constants are interpolated to 15 oC as proposed byGujer et al. (1999). The volumes of the reaction compartments are set as follows: 500 m3 for Reactor 1; 750 m3 for Reactors 2, 3 and 4; 1333 m3 for Reactors 5, 6 and 7. The following constraints are considered for the mass transfer coefficient kLai in each compartment i:kLai=0 for Reactors 1, 2, 3 and 4; 0 <= kLai<= 360d-1 for Reactors 5, 6, and 7. kLai,max=360d-1 is the maximum operating limit.

4.2. Secondary settler model

The secondary settler is modeled as a non-reactive settling tank subdivided into 10 layers of equal thickness, using the double-exponential settling velocity model (Takács et al.1991). A fixed settler depth of 4 m and a cross area of 1500m2 are adopted.

4.3.Splitter and mixer mass balances.

Splitters and mixers models are also needed to represent the proposed superstructure.

4.4.Effluent quality limits

These effluent thresholds values were used as specification constraints (Copp, 2002; Gernaey and Jorgensen, 2004): SNH,ef: 4gNm-3; Ptot ef:1.5gPm-3;NTOT,ef:8gNm-3; BODef: 10 gCOD m-3; CODef:100 gCOD m-3; XSS,ef: 30 gSS m-3.

4.5.Maximum values for operation variables

The maximum values for the operation variables taken from Copp (2002) are: Qr,ext: 36892m3d-1; Qr,int: 92230m3d-1; Qwaste:1844.6m3d-1; uECSD: 2*103 kgCODd-1; kLai:360 d-1.

4.6.Objective Function

The total annual operating cost (OC) is adopted as the objective function to be minimized.The operation cost is computed as follows (Vanrolleghem and Gillot, 2002):

where OCpis the annual operating cost of unit p.EQ, Ea, Epump, uSLDGD and uECSD are the effluent quality index, aeration energy demand, pumping energy demand, waste sludge production rate and external carbon source dosage rate, respectively, which expressions are given in detail in Alasino et al. (2007) and Gernaey and Jorgensen (2004). The annual unitary operation costs are (Vanrolleghem and Gillot, 2002; Mussati et al., 2002; Gernaey and Jorgensen 2004): αEQ: 50 Euro day (kgPU year)-1; αE: 25 Euro daykWh year)-1; αSLDGD: 75 Euro day (kgSS year)-1; αECSD: 109.5 Euro day (kgCOD year)-1.The effluent quality index EQ(kg contaminating unit d-1), which is related to the fines paid due to contaminant discharge, is computed by weighting the compounds loads having influence on the water quality that are usually included in the legislation.

4.7.Influent Wastewater Specifications

The influent WW flow rate is set at 18446 m3 d-1. The influent WW composition used consists of the original flow weighted average dry weather influent composition for ASM1 proposed in COST, modified to make it compatible with the ASM3+BioP model. The influent PO4= concentration (SPO) has been taken from Gernaey and Jorgensen (2004). The nonzero input concentrations for compounds are: SI: 30 gCOD m-3; SS: 69.5 gCOD m-3; XI: 51.2 gCOD m-3 ; XS: 202.32 gCOD m-3; XH: 28.17 gCOD m-3; XSS: 215.493 gSS m-3; SNH: 40.60 gN m-3; SALK: 7 gCOD m-3; SPO4: 9.01 gP m-3.

1. Resultsand Discussion

The resulting mathematical model is a highly non-linear system, formulated as a Nonlinear Programming with Discontinuous Derivatives DNLP, with constraints. The model is used for optimization of the operation conditions for the influent wastewater specifications described in the preceding section. A multiple starting point strategy was adopted and, as expected, several locally optimal solutions were found. The solution showing the minimal OC value is presented. Fig.3shows the optimal configuration and main optimization variable values for the operating conditions for the proposed superstructure. Table 1 shows the main variables optimal values and costs.Optimization models for the conventional processes (A2/O, UCT, modified UCT and Bardenpho process) have also been implemented. These models were developed simultaneously with the superstructure model development in order to validate the preliminary results obtained. These results are presented in Fig.4 and Table 1.

All optimal solutions predict external C source dosage. Reactors resulted to be anaerobic, anoxic or aerobic compartments depending on the DO (SO)and NOx (SNO)concentrations. Fig. 3 shows C source dosage to the 2nd reactor, influent WW distribution to 1st and 2nd compartment, external recycle distribution to 1st and 4th compartment and an internal recycle from the 7th to the 4th one.It presents a zone (1st reactor) with anoxic conditions (SO=8*10-4gm-3; SNO=0.4gm-3) followed by a zone (2nd and 3rd reactors) with anaerobic conditions (SO1*10-5gm-3; SNO=6*10-3 and 4*10-4gm-3), an other zone (4th reactor) with anoxic conditions (SO=1*10-3gm-3; SNO=0.5gm-3), and finally an alternate aerated zone (SO=0.9, 3*10-3 and 0.6gm-3; SNO=9.0, 2.9 and 8.7gm-3). The OC decreases around 7% with respect to the plant and operating conditions proposed by Gernaey and Jorgensen (simulation results not shown), and effluent meets the quality conditions while the last one does not.

Figure3. Optimal configuration and main process variable values

Figure4. Main process variable values for each configuration optimization

In the four configurations of Fig. 4, the internal -i.e. nitrate- recycle from the aerobic zone vanishes. Thus, the anaerobic “character” of the first zone “increases” and so do the P release. Optimal solutions for A2/O and 5-stages Bardenpho process configurations are the same (the differences observed are due to numerical aspects) since the internal recycles vanish: they present a zone (1st and 2nd reactors) with anoxic conditions followed by a zone (3rd and 4th reactors) with anaerobic conditions, and finally an alternate aerated zone. The external C source is added to the anaerobic zone (reactor 3). In VIP and modified UCT configurations the sludge recycle is directed to the 3rd reactor favoring anaerobic conditions in the 1st zone (reactors 1 and 2). The internal recycles coming from the anoxic zone could not be deleted since they are responsible for the biomass addition to the 1st zone. These recycle streams have a low SNOconcentration. As a consequence, in these configurations, the readily biodegradable matter (SS) contained in the effluent and the external C can be use by XPAO (and be more efficiently used for SPO4 release) in the 1st anaerobic zone (reactors 1 and 2), increasing the P-removal efficiency.

The models were implemented and solved using GAMS and CONOPT, respectively.

Table 1. Costs and main variables optimal values

Solution / Superstr. / A2/O / VIP / Mod. UCT / 5 st. Bard.
OC (Euro year-1) / 762 678 / 801 929 / 779 166 / 781 981 / 801 928
EQef(kg PU d-1) / 7 121.22 / 6 904.80 / 6 855.87 / 6 870.22 / 6 910.02
Ea,ef(kWh d-1) / 6 630.72 / 6 970.10 / 6 692.08 / 6 723.81 / 6 970.36
Epump,ef(kWh d-1) / 963.46 / 846.11 / 1 540.15 / 1 476.92 / 843.64
uSLDGD,ef(kgSS d-1) / 2793.95 / 2 929.63 / 2 816.55 / 2 829.37 / 2 929.56
uECSD,ef(kgCODSs d-1) / 65.90 / 379.55 / 176.49 / 194.05 / 377.72
SNH,ef (gN m-3) / 4.00 / 4.00 / 4.00 / 4.00 / 4.00
NTOT,ef (gN m-3) / 13.96 / 13.37 / 13.18 / 13.23 / 13.39
BODef (gCOD m-3) / 2.03 / 2.09 / 2.08 / 2.08 / 2.09
CODef (gCOD m-3) / 46.53 / 46.58 / 46.89 / 46.83 / 46.57
Ptotef (gP m-3) / 1.50 / 1.50 / 1.50 / 1.50 / 1.50
XSS,ef (gSS m-3) / 16.17 / 16.12 / 16.52 / 16.45 / 16.11

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Acknowledgements. The financial support from CONICET and ANPCyT is acknowledged.